Third-Party AI Evals Don't Fix Secrecy, Argues Researcher 1a3orn
1a3orn · x · 2026-09-16
1a3orn argues that letting third-party evaluators into AI labs helps somewhat with principal-agent problems, but does nothing for science or building common knowledge. Quoting labs that call AI super dangerous while refusing to disclose pretraining data, architectures, post-training algorithms, or RL environments, he contends that with everyone "flailing in ignorance," releasing substantive public information matters more right now.
More from AGI Musings
- Nina Schick: who builds intelligence and how it's distributed is the defining question of our lives — NinaDSchick · 2026-10-31
- Cheap intelligence is like cheap bread — an ingredient list satire of mass-produced AI — jsuarez · 2026-10-31
- Two futures for the young in 2026: 511 job rejections by chatbot vs unlimited AI to rebuild Cisco — PeterDiamandis · 2026-10-31
- Terence Tao warns AI is nearing a dangerous threshold as models start cheating — haider1 · 2026-10-31
- Reddit stock plunges 42% in 8 trading days as CEO says AI mode no longer drives traffic — SumitGup · 2026-10-31
- HubSpot co-founder: startups die from suicide, not homicide — competition isn't the real killer — nathanbenaich · 2026-10-31